code: def test_fit():
      oht = TransactionEncoder()
      oht.fit(dataset)
      assert oht.columns_ == [
          "Apple",
          "Bananas",
          "Beer",
          "Chicken",
          "Milk",
          "Rice",
      ]
  
file_path: mlxtend/mlxtend/preprocessing/tests/test_transactionencoder.py
imports: import numpy
  from scipy.sparse import csr_matrix
  from sklearn.base import clone
  from mlxtend.preprocessing import TransactionEncoder
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 1 for calling a global function with example usage: test_fit() without return types